Prerequisites

Before proceeding, ensure you have the following:

• An active Azure account, which can be created at no cost.
• Azure Bicep installed on your local machine.
• Access to the source code available at the following URL, and contributions are welcome!

1. Solution Overview

The solution will encompass the following files:

📄 main.bicep: The primary Bicep template.

📄 main.bicepparam: This parameters file includes values necessary for deploying your Bicep template.

📁 modules: A directory containing additional Bicep files utilized as modules.

The accompanying diagram below illustrates the components that will be deployed:

The architecture diagram above outlines the Azure environment configuration for Azure AI Studio alongside other components, including:

• Hub Workspace: The central workspace connecting various services and resources, serving as the primary management layer.
• Project Workspace: A specific workspace designated for individual projects, enabling the segregation and management of development environments while maintaining a connection to the Hub Workspace.
• Key Vault: Used for securely storing and managing secrets, keys, and certificates.
• Storage Account: This will hold data for files, logs, and necessary datasets, ensuring accessibility for processing and analysis.
• AI Services: This includes various AI services such as Cognitive Services or other AI models.
• Application Insights: Offers monitoring and telemetry data for applications, collecting metrics, logs, and traces.
• Log Analytics: Gathers, analyzes, and visualizes data from multiple sources, including Application Insights.

2. Azure Main Bicep Template

Begin by creating a new file in your working directory, naming it main.bicep. Below is the file's content:

// Parameters

@description('Specifies the name prefix for all Azure resources.')

@minLength(4)

@maxLength(10)

param prefix string = substring(uniqueString(resourceGroup().id), 0, 4)

@description('Specifies the name suffix for all Azure resources.')

@minLength(4)

@maxLength(10)

param suffix string = substring(uniqueString(resourceGroup().id), 0, 4)

@description('Specifies the location for all Azure resources.')

param location string = resourceGroup().location

@description('Specifies the name of the Azure AI Hub workspace.')

param hubName string = ''

@description('Specifies the friendly name of the Azure AI Hub workspace.')

param hubFriendlyName string = 'Demo AI Hub'

@description('Specifies the description for the Azure AI Hub workspace displayed in Azure AI Studio.')

param hubDescription string = 'This is a demo hub for use in Azure AI Studio.'

// Additional parameters...

3. Parameters File

Create another file named main.bicepparam. The code below outlines the definitions for this parameters file:

using './main.bicep'

param aiServicesCustomSubDomainName = ''

param prefix = 'azinsidr'

param suffix = 'test'

param userObjectId = 'your-user-object-id'

// Additional parameters...

4. Deploying the Azure Bicep Template

To deploy your Bicep files, execute the command below:

az deployment group create --resource-group <your-resource-group> --template-file main.bicep --parameters main.bicepparam

Monitor the deployment output, as shown in the image below:

You can confirm the deployment via the Azure Portal.

For a deeper dive into the deployment code, explore the following repositories:

👉 Join the AzInsider email list here.

-Dave R.